As a Deep Learning Compiler Intern, you will work closely with our senior compiler engineers on CGC, Quadric's neural network compiler that lowers to code targeting the Chimera GPNPU. You will dig into real compiler passes — layout selection, memory allocation, operator splitting, code generation — and see your changes flow end-to-end into the C++ that runs on Quadric silicon. This is a hands-on role where you will gain experience designing IR transformations, debugging generated code, and improving how efficiently neural networks map to hardware.

Note: Our preference is for this internship to be based out of our Burlingame, California office. Candidates should be based in the Bay Area or able to relocate for the internship period and available to work on site.

Develop & Implement

Help build and extend compiler passes that lower neural network IR to GPNPU-targeted code.

Diagnose compilation issues by tracing problems from generated C++ back through the pipeline. Use IR dumps and static analyses to investigate compilation failures and performance regressions.

Code Optimization

Work alongside senior engineers to improve compiler decisions to reduce data movement and increase core utilization.

Partner with the kernel, hardware, and data science teams to align compiler features with real model requirements and hardware constraints.

Toolchain Contribution

Contribute to test infrastructure, debugging utilities, and developer ergonomics across the CGC pipeline and runtime.

What Success Looks Like

Within your internship, you'll:

Deep Learning Compiler Intern

Responsibilities

Qualification

Required

Preferred

Company

Quadric

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